Telecommunications signaling practice falls generally into two categories. The first category, digital communication, encodes signals into a series of discrete pulses. The second category, analog communication, is based on modulating a continuous (generally sinusoidal) carrier wave in some way: for example, a signal can be stored in an amplitude modulation to the carrier wave (AM), or in a frequency modulation to the carrier wave (FM).
There is a combination of digital and analog techniques: digital Quadrature Amplitude Modulation (QAM), which conveys a data stream through discrete amplitude modulation of two carrier sine waves 90 degrees out of phase with each other. Euler's formula, which generates the sine and cosine waves, is the basis for most current analog communication techniques, including QAM.
Generally power amplifier architectures trade off efficiency for linearity (e.g., Class A vs. Class D). Consequently, mobile and satellite applications, which need efficient transmission, must use nonlinear amplification techniques. However, for signaling techniques such as QAM to work, amplification should be linear. To overcome such issues, engineers have introduced a multitude of linearization techniques such as pre-distortion, post-distortion, power back-off, feed forward, envelope elimination and restoration, and so forth.
Linear systems may be conceptualized by the whole being the (possibly weighted) sum of the parts, with no need to consider interactions between the parts. Furthermore, standard engineering practice in telecommunications attempts to remove nonlinearity wherever possible. Linear systems are generally easier to design, build and maintain than nonlinear systems. However, the simplicity of linearity comes at a fundamental cost: linear systems are less flexible and therefore less efficient than nonlinear systems. This is why, for example, high performance aircraft such as fighter planes and the Space Shuttle are always highly nonlinear.
Nonlinear efficiency essentially arises from more sophisticated use of available resources. Current telecommunication signaling practice makes simplifying engineering choices that limit performance. For instance, digital pulses control for noise by ignoring all but two amplitude levels, and by making no use of signal shape for signaling purposes. Analog communication (including QAM) is based on a restricted set of manipulations to sine waves.
Furthermore, QAM requires linear power amplification generally due to how QAM signals are generated. Every QAM signal is the linear sum of a cosine and a sine wave of the same frequency but generally different amplitudes. Any such sum is mathematically equivalent to a single sine wave with constant amplitude and shifted phase. Consequently, each QAM signal is inherently and unavoidably transmitted as a sine wave of constant amplitude.
Since nonlinear power amplifiers (NPAs) introduce distortion that varies with amplitude, there is no means to detect, much less correct, such distortion by analyzing signals of constant amplitude. The NPA distortion is mathematically orthogonal to the signal space: no information is shared between them, and hence nothing can be learned of one by studying the other.
Consequently, and despite efforts to compensate for this deficiency, QAM is extremely vulnerable to amplitude distortion. QAM essentially compensates for the lack of varying amplitude information within QAM signals by restricting NPA and separating signals as widely as possible in amplitude space.
Aside from its problems with nonlinear power amplification, another short-corning of QAM is that it is a method based on use of a single frequency: QAM does not make optimal use of the available frequency range. While QAM can be paired with techniques such as Orthogonal Frequency-Division Multiplexing (OFDM) to extend frequency usage, OFDM applied to QAM actually reduces information throughput, rather than increasing it, due to the stringent constraints imposed by signal orthogonality. OFDM is not introduced to improve QAM's efficiency, but rather to compensate for its inherent weaknesses in noise resistance.